In this paper, we illustrate a model-based approach to Web server performance evaluation, and present an analytic queueing model of Web servers in distributed environments. Performance predictions from the analytic model match well with the performance observed from simulation. The model forms an excellent basis for a decision support tool to allow system architects to predict the behavior of new systems prior to deployment, or existing systems under new workload scenarios.

Over the last few years, the World Wide Web has transformed itself from a static content-distribution medium to an interactive, dynamic medium. The Web is now widely used as the presentation layer for a host of on-line services such as e-mail and address books, e-cards, ecalendar, shopping, banking, and stock trading. As a consequence (HyperText Markup Language)HTML files are now typically generated dynamically after the server receives the request. From the Web-site providers' point of view, dynamic generation of HTML pages implies a lesser understanding of the real capacity and performance of their Web servers. From the Web developers' point of view, dynamic content implies an additional technology decision: the Web programming technology to be employed in creating a Web-based service. Since the Web is inherently interactive, performance is a key requirement, and often demands careful analysis of the systems. In this paper, we compare four dynamic Web programming technologies from the point of view of performance. The comparison is based on testing and measurement of two cases: one is a case study of a real application that was deployed in an actual Web-based service; the other is a trivial application. The two cases provide us with an opportunity to compare the performance of these technologies at two ends of the spectrum in terms of complexity. Our focus in this paper is on how complex vs. simple applications perform when implemented using different Web programming technologies. The paper draws comparisons and insights based on this development and performance measurement effort.

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